While the main data graph showed all the relationships among factors, the team's complementary, "sparser" graph showed only what the scientists call conflicts within the data.

In recent years, the Massively Parallel Computation (MPC) model has gained significant attention. However, most of distributed and parallel graph algorithms in the MPC model are designed for ...

Neo4j Aura Graph Analytics comes with more than 65 ready-to-use graph algorithms and is optimized for high-performance AI applications, with support for parallel workflows ensuring any app can ...

Neo4j is an example of a native graph database that was built from the ground up to store pieces of data as nodes and express their connectedness through edges. Xu considers this “Graph 1.0.” The ...

Dr. Alin Deutsch of UC San Diego explains in a Q&A why graph database algorithms will become the driving force behind the next generation of AI and machine learning apps.

Neo4j for Graph Data Science was conceived for this purpose, to improve the predictive accuracy of machine learning, or answer previously unanswerable analytics questions, using the relationships ...

Graph data science is when you want to answer questions, not just with your data, but with the connections between your data points — that’s the 30-second explanation, according to Alicia Frame.